quicklabel

A fast and efficient image labeling tool for creating Text-To-Image finetuning datasets, as taken by the kohya_ss training scripts.

Overview

quicklabel is designed for efficiently creating labeled image datasets in a dreambooth-style format. It simplifies the process of organizing your input images into class directories with accompanying text prompts.

Features

• Simple Workflow: Three-step process for quick dataset organization
• Class Management: Create custom classes with configurable repeat parameters
• Prompt Templates: Pre-fill prompts to speed up repetitive labeling
• Trash Option: Easily discard unwanted images

Installation

From Cargo

cargo install quicklabel

From Releases

Visit the Releases page and download the latest executable for your platform.

Usage

1. Directory Setup

First, configure your directories:

• Input Directory: Folder containing unlabeled images
• Output Directory: Root folder where class directories will be created
• Trash Directory (Optional): Where discarded images are moved. If not specified, they will remain in the input directory when discarded.

2. Class Configuration

Define your classes:

• Enter a class name and number of repeats
• The output folders will be created as {repeats}_{class_name}
• Optionally configure a prompt template that will be pre-filled during labeling

3. Image Labeling

Process your images:

• View each image and enter a prompt (or use the pre-filled template)
• Select a class by clicking its button
• Images are moved to the appropriate class folder with matching text files
• Use the "Trash" button to discard unwanted images

License

Copyright © 2025, sysrqmagician sysrqmagician@proton.me

Licensed under the terms included in the LICENSE file.